Abstract

The Geostationary Operational Environmental Satellite R (GOES-R) series of four satellites are the next generation NOAA GOES satellites. Once on orbit and commissioned, they are renamed GOES 16–19, making critical terrestrial and space weather measurements through 2035. GOES 16 and 17 are currently on orbit, having been launched in 2016 and 2018, respectively. The GOES-R satellites include the Extreme Ultraviolet (EUV) and X-ray Irradiance Sensors (EXIS) instrument suite, which measures calibrated solar irradiance in eight lines or bands between 25 nm and 285 nm with the Extreme Ultraviolet Sensors (EUVS) instrument. EXIS also includes the X-Ray Sensor (XRS) instrument, which measures solar soft X-ray irradiance at the legacy GOES bands. The EUVS Measurements are used as inputs to the EUVS Model, a solar spectral irradiance model for space weather operations that predicts irradiance in twenty-two 5 nm wide intervals from 5 nm to 115 nm, and one 10 nm wide interval from 117 to 127 nm at 30 s cadence. Once fully operational, NOAA will distribute the EUVS Model irradiance with 1 min latency as a primary space weather data product, ushering in a new era of rapid dissemination and measurement continuity of EUV irradiance spectra. This paper describes the EUVS Model algorithms, data sources, calibration methods and associated uncertainties. Typical model (relative) uncertainties are less than ~5% for variability at time-scales longer than 6 h, and are ~25% for solar flare induced variability. The absolute uncertainties, originating from the instruments used to calibrate the EUVS Model, are ~10%. Examples of model results are presented at both sub-daily and multi-year timescales to demonstrate the model’s capabilities and limitations. Example solar flare irradiances are also modeled.

Highlights

  • Solar Extreme Ultraviolet (EUV, 10–121 nm) irradiance is the primary energy input into the Earth’s upper atmosphere at low to mid latitudes and at all latitudes during geomagnetically quiet periods

  • Regular sub-daily EUV measurements made by the Solar EUV Experiment (SEE) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite were incorporated into the Flare Irradiance Spectral Model (FISM) developed by Chamberlin et al (2007)

  • The Extreme Ultraviolet Sensors (EUVS) model coefficients determined here from irradiance measurements made during Solar Cycles 23 and 24 are expected to apply to future solar cycles because the relationship between EUV emissions and the thermal structure of the solar atmosphere are expected to be invariant between solar cycles

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Summary

Introduction

Solar Extreme Ultraviolet (EUV, 10–121 nm) irradiance is the primary energy input into the Earth’s upper atmosphere at low to mid latitudes and at all latitudes during geomagnetically quiet periods. Solar EUV and Far Ultraviolet (FUV, 122–200 nm) irradiance is completely absorbed in the Earth’s upper atmosphere, requiring it to be measured by sophisticated space-based instrumentation that is prone to degradation This measurement difficulty has resulted in extended periods of time when direct spectral irradiance measurements are unavailable, necessitating models of solar EUV and FUV irradiance to bridge the observational gaps. Regular sub-daily EUV measurements made by the Solar EUV Experiment (SEE) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite were incorporated into the Flare Irradiance Spectral Model (FISM) developed by Chamberlin et al (2007). FISM was recently updated by Thiemann et al (2017a) to use measurements from the EUV Monitor (EUVM) onboard the Mars Atmosphere and EvolutioN (MAVEN) probe as inputs and included spectral irradiance data from the EUV Variability Experiment (EVE) onboard the Solar Dynamics Observatory (SDO) in the model calibration dataset.

Model description
Historical datasets
EXIS cross-calibration with historical datasets
Model uncertainties
Long-term model formulation
Long-term model component results
Short-term model formulation
Short-term model component results
Findings
Discussion
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